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All Journal Indonesian Journal of Information System Jurnal Responsif : Riset Sains dan Informatika Journal of Software Engineering and Information System (SEIS)
Dyah Mustikasari
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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SUPPORT VECTOR MACHINE ALGORITHM FOR EARLY DETECTION SYSTEM FOR MENTAL EMOTIONAL DISORDERS IN ADOLESCENTS Muthya Cahyani Putriabhimata; Ida Widaningrum; Dyah Mustikasari
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 5 No. 1 (2025)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v5i1.8351

Abstract

A mental-emotional disorder is a condition characterized by emotional fluctuations that, if left untreated, might progress into an abnormal state. In Indonesia, the treatment of mental problems is infrequently conducted due to a scarcity of psychiatric personnel and the high expenses associated with comprehensive mental health therapy and treatment. An early detection system for mental-emotional illnesses in teenagers was developed by implementing the Support Vector Machine (SVM) algorithm as a solution to this issue. The Support Vector Machine algorithm is a very accurate classification approach. This study utilizes data that is categorized into two distinct groups: anxiety and depression. The data is partitioned in an 80:20 ratio, with 80% allocated for training data and 20% for test data. The research findings indicate that the testing accuracy levels yielded a value of 85%. The value is derived using the RBF kernel with a gamma value of 0.1 and a C value 10. The Support Vector Machine model is implemented within the Graphical User Interface (GUI). The user experience questionnaire was assessed on the Graphical User Interface, resulting in a user experience score within the "good" category.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN DOMPET DIGITAL MENGGUNAKAN METODE ANALYTIC HIERARCHY PROCESS (AHP) Widaningrum, Ida; Dinda Septyana; Dyah Mustikasari
Jurnal Responsif : Riset Sains dan Informatika Vol 7 No 1 (2025): Jurnal Responsif : Riset Sains dan Informatika
Publisher : LPPM Universitas Adhirajasa Reswara Sanjaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51977/jti.v7i1.1801

Abstract

Dalam era fintech yang berkembang pesat, dompet digital menjadi solusi keuangan yang penting namun membingungkan pengguna akibat banyaknya pilihan dan fitur. Penelitian ini bertujuan merancang dan mengimplementasikan Sistem Pendukung Keputusan (SPK) untuk pemilihan dompet digital menggunakan Metode Analytic Hierarchy Process (AHP). Dengan AHP, penelitian ini menganalisis kriteria seperti keamanan, kemudahan penggunaan, transaksi dengan merchant lain, dan pelayanan penyedia layanan untuk memberikan rekomendasi yang akurat. Hasil penelitian ini diharapkan membantu pengguna dalam membuat keputusan yang lebih terinformasi dan efisien dalam memilih dompet digital yang sesuai dengan kebutuhan mereka. Kesimpulannya, SPK berbasis AHP ini mampu memberikan rekomendasi yang lebih objektif dan dapat diandalkan, sehingga mempermudah pengguna dalam menentukan pilihan dompet digital yang optimal.
Recognition of the Lima Pandawa Shadow Puppet characters utilizing Principal Component Analysis (PCA) for feature extraction and K-Nearest Neighbor (KNN) for classification Ida WIdaningrum; Indah Puji Astuti; Dyah Mustikasari; Khoiru Nurfitri; Rifqi Rahmatika Az-Zahra; Rhesma Intan Vidyastari; Ali Selamat
Indonesian Journal of Information Systems Vol. 8 No. 1 (2025): August 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v8i1.11032

Abstract

The traditional type of puppet-shadow play, Wayang Kulit, is an integral component of Indonesian culture. The Pandawa Lima, protagonists in this artistic medium, have great importance not just in narrative but also in embodying moral and ethical principles. The automated identification of these characters can optimize a range of applications, such as instructional resources, digital preservation, and interactive displays. This research intends to maximize the advantages of PCA and KNN by utilizing their respective strengths: PCA's capacity to decrease data dimensionality and KNN's efficacy in classification tasks. An expected outcome of this combination is an enhancement in recognition accuracy without compromising computational efficiency. The classification matrix indicates that the model achieved a 78% accuracy rate. Class-specific accuracy, recall, and F1-scores are as follows: arjuna achieves a precision of 0.85, recall of 0.91, and F1 Score of 0.87. Macro averages for precision, recall, and F1 are 0.77, 0.76, and 0.74, respectively. Weighted averages for these metrics are 0.80, 0.78, and 0.77, respectively. The model exhibits strong performances on Arjuna, Sadewa, and Yudistira, but encounters difficulties with Bima and Nakula.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN DOMPET DIGITAL MENGGUNAKAN METODE ANALYTIC HIERARCHY PROCESS (AHP) Widaningrum, Ida; Dinda Septyana; Dyah Mustikasari
Jurnal RESPONSIF: Riset Sains & Informatika Vol 7 No 1 (2025): Jurnal Responsif : Riset Sains dan Informatika
Publisher : LPPM Universitas Adhirajasa Reswara Sanjaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51977/jti.v7i1.1801

Abstract

Dalam era fintech yang berkembang pesat, dompet digital menjadi solusi keuangan yang penting namun membingungkan pengguna akibat banyaknya pilihan dan fitur. Penelitian ini bertujuan merancang dan mengimplementasikan Sistem Pendukung Keputusan (SPK) untuk pemilihan dompet digital menggunakan Metode Analytic Hierarchy Process (AHP). Dengan AHP, penelitian ini menganalisis kriteria seperti keamanan, kemudahan penggunaan, transaksi dengan merchant lain, dan pelayanan penyedia layanan untuk memberikan rekomendasi yang akurat. Hasil penelitian ini diharapkan membantu pengguna dalam membuat keputusan yang lebih terinformasi dan efisien dalam memilih dompet digital yang sesuai dengan kebutuhan mereka. Kesimpulannya, SPK berbasis AHP ini mampu memberikan rekomendasi yang lebih objektif dan dapat diandalkan, sehingga mempermudah pengguna dalam menentukan pilihan dompet digital yang optimal.
Co-Authors Ali Selamat Dinda Septyana Ida Widaningrum, Ida Indah Puji Astuti Khoiru Nurfitri Muthya Cahyani Putriabhimata Rhesma Intan Vidyastari Rifqi Rahmatika Az-Zahra